It can be difficult to manually monitor complex machines that have several moving and/or vibrating parts (e.g., turbines, compressors, and the like). Monitoring systems can be commonly used to monitor the operation of complex machines, and generate alarms when the machine is not operating as desired. Monitoring systems can include sensors to detect operational information (e.g., operating parameters, operational states, and the like) associated with the machines, and relay a signal to a computing device, which can visually present the operational information for a designated personnel. For example, a turbine can include an accelerometer that can monitor the motion of blades of a turbine and relay angular velocity measurements to a computer for visualization.
Operational information of a complex machine can include information related to multiple operational parameters and multiple operational states of the machine. For example, Operational states can include a state in which the machine is starting up or shutting down (“startup-shutdown state”), state of normal operation (“running state”), state in which the machine is turned off (“machine off state”), and the like. The operating parameters of the various operational states can include, turbine angular velocity, machine-part vibration rate, and the like. The computing device can automatically generate alarms to identify undesirable behavior of the machine, which can transition through multiple operational states. These alarms can be generated based on alarm triggers or set points, which can include conditions that can be uniquely configured for the different operational states of a machine. Graphical representation of generated alarms along with operational information of the machine in a graphical display can be valuable for understanding trends in machine operation. However, as the machine transitions through multiple operational states, multiple alarms can be generated for each state. As a result, the graphical display can become cluttered and deciphering operation trends can become challenging.